The primary goal of this project is to improve the clinical outcomes of hepatic radiofrequency ablation (RFA) therapy using state-of-the-art computer visualization techniques. We hypothesize that physicians will be more accurate in targeting RFA therapy to hepatic tumors using a contextually-correct three-dimensional (3D) visualization system than they could be with standard two-dimensional ultrasound alone. If proven beneficial, this technique could be used to decrease the post-RFA tumor recurrence rate (currently 33-48%) and improve the lives of thousands of patients with hepatic tumors annually. This study will proceed through four major phases of research: validation of our quantitative RFA phantom and segmentation methods; a large, randomized controlled trial comparing several methods of RFA guidance using our RFA phantoms; a randomized, controlled trial using the woodchuck model of hepatocellular carcinoma; and, a small randomized, controlled trial of safety and efficacy in humans. In addition, we will conduct several technical and synergistic research efforts, including improving the calibration of clinical display systems, developing fully automatic, continuous calibration methods for such systems, and determining the efficacy of enhanced guidance systems for teaching RFA techniques to novice physicians. The most immediate potential benefit of this research could be reduced tumor recurrence near RFA sites because of more accurate placement and estimation of the ablation zone boundaries. This research will also serve as the groundwork for the development of more sophisticated guidance systems to enable treatment of large and more complex lesions. Because of the similarity of this placement task to many other clinical ablation or biopsy tasks, we expect that these results would have applicability well beyond hepatic RFA. Finally, we may find that this system is effective for training novice users in the conduct of spatially complex procedures like RFA. This study will also provide two (2) important therapeutic research tools that are currently lacking for RFA: a quantitative accuracy phantom and a large animal model for in vivo hepatic tumors. The quantitative phantom will allow groups to evaluate new techniques for accurate RFA placement and ablation zone prediction and measurement. The woodchuck model will allow for more realistic in vivo experimentation as a step before human studies.